Current PhD Students

Student Leadership

Student Chairs

Diversity, Equity, and Inclusion Chair: Kriti Agrawal (faculty mentor: Smita Krishnaswamy)
Outreach Chair: Yaro Markov (faculty mentor: David van Dijk)
Peer Mentorship Coordinator: Cole Jensen (faculty mentor: Robert McDougal)
Social Chair: Vimig Socrates (faculty mentor: Steven Kleinstein)

Student Government

GSA Representative: Kyra Thrush
GPSS Senator: Evan Cudone
GPSS Senator: J. Nick Fisk

Daniel Chawla - Kleinstein lab (2015) | ORCID: 0000-0001-7667-9337
Daniel Chawla's picture
Nir Neumark - Kaminski lab & Coifman lab (2016) | ORCID: 0000-0002-5560-6136
Jiawei Wang - Zhao lab (2016) | ORCID: 0000-0003-2627-4897

Jiawei’s research interest lies in imaging genetics and mental diseases. He is working on gene expression analysis to help discover the etiology of PTSD and graphical models to study brain functional and structural network. 

Zhaolong Yu - Zhao lab (2016) | ORCID: 0000-0001-9585-2465
Zhaolong Yu's picture

Zhaolong’s current research focus is patient outcomes prediction based on multi-omics data. He is particularly interested in developing machine learning algorithms to better predict cancer patient outcomes.

Evan Cudone - McDougal lab (2017) | ORCID: 0000-0002-1055-1645
Evan Cudone's picture

Evan utilizes natural language processing and machine learning to facilitate computational neuroscience research. Using unsupervised topic modeling and deep learning language models he characterizes neuroscience simulation research from its academic literature and source code.

J. Nick Fisk - Townsend Lab (2017) | ORCID: 0000-0002-1940-393X
J. Nick Fisk's picture

Nick works on constructing phylogenetic trees to answer questions about cancer development, evolution, and the selective pressure treatment induces on the system. He also works on developing and implementing methods to optimize general phylogenetic experimental design.

Jiahao Gao - Gerstein lab (2017) | ORCID: 0000-0002-6311-3526

Jiahao focuses on the analysis of high throughput sequencing data, with special interest in ChIP-seq and other functional genomics technologies. He is currently working on denoising the ChIP-seq binding sites in order to improve the de novo inference of transcription factor binding motifs.

Pranav Kantroo - Wagner lab & Machta lab (2017)
Tianxiao Li - Gerstein lab (2017) | ORCID: 0000-0002-9147-7511

Tianxiao is interested in applying novel machine learning techniques to inference of gene regulatory networks and 3D genomics. He is now working on developing novel methods to associate 3D genomics structures with gene regulatory elements.

Wei Liu - Zhao lab (2017) | ORCID: 0000-0003-2558-1377
Wei Liu's picture

Wei’s research is mainly focused on understanding genetic architecture and mechanisms of complex diseases. She is now working in developing statistical methods investigating disease-associated genes using multi-omics data including genetics, epigenetics and transcriptomics data. Wei is also interested in population genetics and causal inference.

Rihao Qu - Kluger lab & Flavell lab (2017) | ORCID: 0000-0002-8258-8287

Rihao’s research interests include high-throughput sequencing analysis and immunogenomics. He is working on developing computational and statistical methods to process high-dimensional single cell sequencing data and help understand the genetic mechanisms underlying immune pathways.

Yixuan Ye - Zhao lab (2017) | ORCID: 0000-0002-2643-665X
Yixuan Ye's picture

Yixuan’s research focuses on the genetic risk prediction for chronic diseases and cancer. She is currently working on exploring the interaction between gene, lifestyle and diseases. She is also interested in developing new methods to improve genetic prediction accuracy and the interpretation of polygenic risk score. 

Geyu Zhou - Zhao lab (2017) | ORCID: 0000-0002-4049-0193

Geyu’s research interest is statistical genomics and genetics. He is experienced in gene expression data analysis. He is currently working on developing statistical methods to compute polygenic risk score.

Edel Aron - Kleinstein lab (2018) | ORCID: 0000-0002-8683-4772
Edel Aron's picture

Edel’s research is focused on developing novel computational methods capable of inferring networks of interactions present in the skin lesions of patients with Lyme disease. Her goal is to better understand the nature of the lesions and the full immunological response to the disease as well as to be able to predict its clinical course.

Egbert Castro - Krishnaswamy lab (2018) | ORCID: 0000-0001-7883-5241
Egbert Castro's picture

Egbert is interested in developing improved methods for biomolecule representation, particularly with the goal of better connecting structure-property relationships. In this pursuit, his work combines methods from machine learning as well as graph signal processing to build more predictive and interpretable representations of entities such as small molecules or proteins.

Alex Grigas - O'Hern lab (2018) | ORCID: 0000-0002-1588-2996
Alex Grigas's picture

Alex is interested in the statistical mechanics of protein structure and his current research project is focused on protein decoy detection, which involves developing scoring metrics to distinguish real protein structures from erroneous ones generated using computational protein design software.

Jeff Mandell - Townsend lab (2018) | ORCID: 0000-0002-3839-2543
Jeff Mandell's picture

Jeff is currently studying the somatic evolution of cancer with the goal of guiding treatment plans and drug development. More broadly, Jeff is interested in developing tools and methods to organize large amounts of heterogeneous genomics data into coherent biological knowledge.

Kyra Thrush - M. Levine lab (2018) | ORCID: 0000-0002-3991-9597

Kyra’s research revolves around the epigenetic patterning that exists as a result of the aging process. In particular, she is developing biomarkers to predict incidence and severity of cognitive impacts in Alzheimer’s dementia, a disease highly associated with human aging.

Ana Berthel - Gerstein lab (2019) | ORCID: 0000-0001-6849-982X
Jeremy Gygi - Kleinstein lab (2019) | ORCID: 0000-0001-8567-7472
Jeremy Gygi's picture

Jeremy is interested in developing novel holistic computational methods that work with multi-omics datasets. Specifically, he is working on improving multi-omic data integration through the use of latent factor models.

Wes Lewis - Kluger lab (2019) | ORCID: 0000-0002-1192-8862
Yaroslav Markov - M. Levine lab (2019) | ORCID: 0000-0001-8778-4909
Yaroslav Markov's picture

Yaroslav is studying the molecular mechanisms behind organismal aging with the ultimate goal of developing strategies to modulate this universal process. He is especially interested in the role of somatic mutations in age-related dysregulation of gene expression and uses machine learning to better understand it.

Eric Ni - Gerstein lab (2019) | ORCID: 0000-0002-4530-0707

Eric is interested in applications of image processing and deep learning techniques for genome privacy and cryo-EM. He is currently working on analysis of privacy leakage from histopathology images and development of upscaling algorithms for cryo-EM structures.

Vimig Socrates - Brandt lab (2019) | ORCID: 0000-0001-7955-9875
Vimig Socrates's picture

Vimig is interested in clinical knowledge representation, NLP, and patient representations. He is currently working on a project in automated EHR data curation.

Andrea Tamminga - Cotsapas lab (2019) | ORCID: 0000-0001-9049-0928
Andrea Tamminga's picture

Andrea’s focus is on determining the effects of gonadocorticoid levels on the risk of developing autoimmune diseases, such as multiple sclerosis, as well as understanding the fundamental differences in immune function between males and females.

Aarthi Venkat - Krishnaswamy lab (2019) | ORCID: 0000-0003-0298-0172
Aarthi Venkat's picture

Aarthi is interested in developing improved methods to study cancer immunogenomics. To this end, her research focuses on machine learning and graph-based methods that leverage the rich properties of single-cell RNA sequencing data.

Mamie Wang - Kleinstein lab & Kluger lab (2019) | ORCID: 0000-0002-3453-7805
Mamie Wang's picture

Mamie is interested in computational immunology and developing new methods for analyzing single-cell datasets to better understand immune responses. Currently, she is working on projects investigating how B cells respond to flu vaccination. 

Junchen Yang - Kluger lab (2019) | ORCID: 0000-0003-0988-1564

Junchen’s major interest is developing and applying computational methods to analyze high-dimensional transcriptomic data. He is also interested in tackling emerging sequencing protocol-oriented questions.  Currently, he is working on cell-interaction interpretations from single-cell RNA-sequencing data, and feature selection problems using novel deep learning methods.

Seyedeh Maryam Zekavat - Zhao lab (2019) | ORCID: 0000-0003-4026-8944
Maryam is a MD-PhD student interested in combining germline and somatic genomics with deep phenotyping to discover and understand the causal factors of disease.
Biqing Zhu - Zhao lab (2019) | ORCID: 0000-0002-7428-6297
Biqing Zhu's picture

Biqing’s research focuses on single cell data modeling and analysis to better understand its underlying structure and find biologically meaningful signals. And she is currently working on developing statistical methods to conduct CyTOF data clustering through multi-omics data deconvolution. 

Sarah Dudgeon - Schulz lab (2020)
Noah Yann Lee - Kleinstein lab (2020)
Noah Yann Lee's picture
Jason Liu - Gerstein lab (2020) | ORCID: 0000-0001-7197-7319

Jason’s research focuses on leveraging genomics and biosensor/wearable data to better understand disorders and diseases related to the brain. Specifically, he uses novel deep learning and statistical approaches to find the underlying biological differences between various phenotypes.

A Ram - Crawford lab (2020)

A is interested in epidemiological problems related to population health in carceral settings [prisons, halfway houses etc] and substance use. At the moment they are developing novel causal inference techniques to identify and understand factors that have contributed to opioid-related overdose deaths in Connecticut from 2009 to 2019. 

Raghav Sehgal - M. Levine lab (2020)
Raghav Sehgal's picture

Raghav’s research focuses on understanding Human Aging. Through his research Raghav is trying to answer critical questions such as “What are the biological systems and processes driving human aging?”, “How can we measure biological aging?”, “Can we reverse the processes driving Aging?” and “How does Aging give rise to diseases like Cancer, Diabetes, Alzheimer’s and more?”. To answer these questions, Raghav is building deep learning tools and techniques using multi-omic (Epigenetics, Transcriptomics, Proteomics, Metabolomics et al) and multi-modal data (Whole body and Organular Biomarkers, Tissue Omics and Single-Cell Omics).

Michelle Yu - (2020) | ORCID: 0000-0003-0307-530X
Kriti Agrawal - Kluger lab & Flavell lab (2021)
Donglu Bai - (2021) | ORCID: 0000-0002-4800-732X
Yuhang Chen - Gerstein lab (2021) | ORCID: 0000-0001-9906-4108
Mingze Dong - Kluger lab & Fan lab (2021) | ORCID: 0000-0001-7367-6819
Cole Jensen - Kleinstein lab (2021)
Andrew Jia - Cotsapas lab (2021)
Yunzhe Jiang - Gerstein lab (2021) | ORCID: 0000-0001-8768-0050
Huan Li - Melnick lab (2021)
Ruiqi Li - Kluger lab (2021)
Jake Sumner - O'Hern lab (2021)
Xin Xin - Gerstein lab & Krumholz lab (2021) | ORCID: 0000-0002-0223-923X